Description
Data Science and Machine Learning program is an instructional class from Leading platform to learn computer programming "E-learn Programming" is that you need to totally with information science and AI natural and makes innovation like Tensorflow., the python, learning, and … relapse, and so forth grouping, neural organizations, and artificial intelligence to preparing.
In the event that you have no information in the field of AI and data science purposes. this period, the main points fundamental disclose to you, and afterward give the high-level strategies and work on various ventures, you to the expert level brings.
This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture, this is one of the most comprehensive courses for data science and machine learning.
- Programming with Python
- NumPy with Python
- Using pandas Data Frames to solve complex tasks
- Use pandas to handle Excel Files
- Web scraping with python
- Connect Python to SQL
- Use matplotlib and seaborn for data visualizations
- Use plotly for interactive visualizations
- Machine Learning with SciKit Learn, including:
- Linear Regression
- K Nearest Neighbors
- K Means Clustering
- Decision Trees
- Random Forests
- Natural Language Processing
- Neural Nets and Deep Learning
- Support Vector Machines
and much, much more!
Why Should You Learn Data Science & Machine Learning?
| In-Demand Skills | The demand for talents in Data Science and Machine Learning is substantial across many industries, presenting promising employment opportunities. |
| Data-Driven Decision Making | Data Science plays a crucial role in enabling businesses to make well-informed decisions by utilizing data analysis and extracting valuable insights. |
| Predictive Analytics | Machine Learning facilitates the generation of forecasts and predictions, thereby providing businesses with the ability to actively prepare for and react to emerging trends. |
| Automated Decision Systems | Machine Learning models have the capability to automate decision-making processes, hence enhancing operational efficiency. |
| Personalization | Data Science and Machine Learning (ML) play a crucial role in enabling customized user experiences within various apps and services. |
| AI-Powered Innovations | Machine Learning plays a pivotal role in facilitating advancements in Artificial Intelligence by enabling the development of innovative solutions in domains such as natural language processing and computer vision. |
| Extracting Insights | The field of Data Science facilitates the extraction of significant insights from extensive datasets, hence enhancing comprehension. |
| Optimizing Processes | Machine learning (ML) techniques have been employed to enhance process optimization, leading to increased efficiency and cost reduction. |
| Competitive Advantage | The adoption of Data Science and Machine Learning confers a competitive advantage in the modern age of digitalization. |
| Continuous Learning | In the field of data science and machine learning, professionals are presented with the prospect of ongoing education and advancement within a dynamic domain. |
What you'll learn?
- Become a Data Scientist and get hired
- Master Machine Learning and use it on the job
- Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
- Use modern tools that big tech companies like Google, Apple, Amazon and Facebook use
- Present Data Science projects to management and stakeholders
- Learn which Machine Learning model to choose for each type of problem
- Real life case studies and projects to understand how things are done in the real world
- Learn best practices when it comes to Data Science Workflow
- Implement Machine Learning algorithms
- Learn how to program in Python using the latest Python 3
- How to improve your Machine Learning Models
- Learn to pre-process data, clean data, and analyze large data.
- Build a portfolio of work to have on your resume
- Developer Environment setup for Data Science and Machine Learning
- Supervised and Unsupervised Learning
- Machine Learning on Time Series data
- Explore large datasets using data visualization tools like Matplotlib and Seaborn
- Explore large datasets and wrangle data using Pandas
- Learn NumPy and how it is used in Machine Learning
- A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
- Learn to use the popular library Scikit-learn in your projects
- Learn about Data Engineering and how tools like Hadoop, Spark, and Kafka are used in the industry
- Learn to perform Classification and Regression modeling
- Learn how to apply Transfer Learning
Course Duration
- 120 Lectures and 52 Hours of on Demand HD Videos
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
- 2500+ students enrolled
- Complete Practical Training
- Download access
- Watch Videos in Android and iOS App
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